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How First- and Third-Party Data Can Supercharge Your Marketing Strategy

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How First- and Third-Party Data Can Supercharge Your Marketing Strategy

Ben Shipley, Chief Innovation Officer, Ovato

We find ourselves in an era of Big Data and as a business, it’s highly likely that you’ve been sitting on a gold mine.

Customer data is your best friend, a potentially unmined resource that can help you better understand your audience, predict future behaviour and enable real-time marketing decisions.

What is a data-driven strategy and why is it important?

A data-driven marketing strategy is built on insights gained through a rigorous analysis of your data, to more accurately target customers and increase the chances of successfully converting their business. Put simply, you can use resources you already have available (your customer data) to dramatically increase the effectiveness of your marketing, simply by asking the right questions.

With insights to back up your decision making, you can deliver your marketing messages to the right people, in the right place, at the right time.

Start simple: use your first-party data

Where to begin? With the data you already own. This is called first party data.

Broadly speaking, first party data is collected simply by doing business and interacting with your customers and audience. There are many places you can source this from, including your CRM platform, surveys, customer feedback and so on. It doesn’t cost a thing to capture, because you already have it, but it will take effort and cost to make it useful.

Let’s say as an example that you’re regularly sending email newsletters to your customers. From this interaction, there’s a raft of useful insights to be found including which customers open what emails, when people are at their most active, what topics your audience is most interested in, what type of content generates actions and so on.

Before you start looking at your data, ask yourself what you’re hoping to achieve. Are you looking to increase sales? Boost your conversion rates? Get more efficient with your marketing spend? Whatever it is, the important thing is nailing the question. Clear objectives make it easier to view your data through an objective lens. This ensures the data is working for you, and not simply reinforcing a preconceived issue or belief.

There’s one big caveat to be aware of: of you didn’t know you were sitting on a goldmine, it’s likely your data is spread out across disparate systems. There are two big challenges that await you. First, ensuring the data can be consistently evaluated. Hygiene has been a painful task for many businesses, and while applications like AWS Glue offer hope for an automated future, there’s still a considerable work involved. Second, your data capture practices probably aren’t great. This could manifest in your production data having 50 per cent of the jobs categorised as “other” or fields missing. You’ll need to lead a cultural change to shift behaviours and ensure you capture the best record possible, from here on out at least.

The fantastic four

Data sets are increasingly massive in size, and only getting bigger as businesses collect more and more information. To make sense of all of this, Artificial Intelligence (AI) and Machine Learning (ML) technologies will become more ingrained in everyday marketing practices, with IDC predicting companies will spend $57 billion on AI platforms by 2021. With that kind of uptake, it’s worth considering how you can organise your data to take advantage of AI and ML.

Look for datasets with these attributes if you’re looking to take advantage of the rise of the machines in helping shape your business strategy and opportunity:

1. Volume – The more data you have, the better the predictive ability.

2. Variety – Ideally, you want your data to include variety such as different accounts, audiences, store locations, or sources.

3. Granularity – The different attributes found within the data. In other words, the ‘grit’ or detail.

4. Trend – A long time scale, or data gathered over a year or more, to allow for seasonal trends and anomalies.

Reap the benefits of a second or third party

First party data alone doesn’t show you the entire picture.

This is where second- and third-party data sourced from outside your business, such as real customer level transactions or addresses of Australian consumers, can power up your marketing strategy.

By marrying your data with others, you gain an understanding of what’s going on in the rest of the market, not just your own backyard.

For example, you may have a wealth of data based on geography, such as catalogue readers, store foot traffic or local memberships. You can then apply third party transaction data that shows how customers are spending, and what on, to enhance the value of that. Or even use publicly accessible Census data to understand the typical attributes of an audience that lives in different locations across Australia.

When you have a record of where you have distributed a catalogue or other marketing material, third party data can measure the quantifiable impact on in-store purchases. In other words, your data set can be matched with another data set to create a model of proof.

Making sense of the data

Having access to all this data is useless if you can’t understand it. Many organisations won’t have access to data scientists, making effective visualisation crucial. With easy visualisations of the trends present in your data, you can recognise patterns more easily than scrolling through an Excel file with thousands of entries, helping you to make informed decisions as a result – whether you’re a CMO, brand manager, financial analyst or sales team account lead.

Visualisation isn’t just about graphs and charts that look good on a screen. The most effective tools will allow you to overlay different sets of data, such as sales and campaign data, use filters to choose the information most important to you, and view both 2D and 3D maps to bring it all to life and allow for more thorough interrogation. Locating specific audience segments and insights is simple when you’re able to filter quickly by data sources, demographic info or store.

The end results

Determining the model of proof isn’t the end of the process. Sure, you’ve combined your data sets and concluded that your marketing efforts are or aren’t working, but you can’t just sit back and say, “Our strategy worked!” You need to go a step further and ask yourself, “If it worked like this, let’s change these aspects of it and see if we can make it work better.”

The true value of a data-driven strategy is actionable insights, giving your business the ability to create proper change, reduce wasted spend, and measurably increase the success rate of your marketing efforts.